Graph-of-word: Boosting Text Mining with Graphs

Michalis Vazirgiannis Laboratory of Informatics, Ecole Polytechnique, France

mvazirg@lix.polytechnique.fr

ABSTRACT The Bag-of-words model has been the dominant approach for IR

and Text mining for many years assuming the word independence

and the frequencies as the main feature for feature selection and

for query to document similarity. Although the long and

successful usage, bag- of-words ignores words’ order and distance

within the document – weakening thus the expressive power of the

distance metrics. We propose graph-of-word, an alternative

approach that capitalizes on a graph representation of documents

and challenges the word independence assumption by taking into

account words’ order and distance. We applied graph-of-word in

various tasks such as ad-hoc Information Retrieval, Single-

Document Keyword Extraction, Text Categorization and Sub-

event Detection in Textual Streams. In all cases the the graph of

word approach, assisted by degeneracy at times, outperforms the

state of the art base lines in all cases.

Author Keywords Graph Mining, Text Mining, Graph Degeneracy

BIOGRAPHY Dr. Vazirgiannis is a Professor at LIX, Ecole Polytechnique

in France. He has conducted research in GMD-IPSI, Max

Planck MPI (Germany), in INRIA/FUTURS (Paris). He has

been a teaching at AUEB (Greece), Ecole Polytechnique,

Telecom-Paristech, ENS (France), Tsinghua (China) and in

Deusto University (Spain). His current research interests are

on machine learning and combinatorial methods for Graph

analysis (including community detection, graph clustering

and embeddings, influence maximization), Text mining

including Graph of Words, word embeddings with

applications to web advertising and marketing, event

detection and summarization. He has active cooperation

with industrial partners in the area of data analytics and

machine learning for large scale data repositories in

different application domains. He has supervised fourteen

completed PhD theses. He has published three books and

more than a 140 papers in international refereed journals

and conferences. He has organized large scale conferences

in the area of Data Mining and Machine Learning (such as

ECML/PKDD) while he participates in the senior PC of AI

and ML conferences – such as AAAI and IJCAI, He has

received the ERCIM and the Marie Curie EU fellowships

and since 2015 he leads the AXA Data Science chair.

REFERENCES 1. Christos Giatsidis, Dimitrios M. Thilikos, Michalis

Vazirgiannis: D-cores: Measuring Collaboration of Directed

Graphs Based on Degeneracy. IEEE - ICDM 2011: 201-210

2. Matching Node Embeddings for Graph Similarity, Giannis

Nikolentzos, Polykarpos Meladianos and Michalis

Vazirgiannis, AAAI2017

3. Konstantinos Skianis, François Rousseau, Michalis

Vazirgiannis: Regularizing Text Categorization with Clusters

of Words. EMNLP 2016: 1827-1837

4. A. J.-P. Tixier, Fragkiskos D. Malliaros, Michalis

Vazirgiannis: A Graph Degeneracy-based Approach to

Keyword Extraction. EMNLP 2016: 1860-1870

5. GoWvis: a web application for Graph-of-Words-based text

visualization and summarization, AJP Tixier, K Skianis, M

Vazirgiannis ACL 2016, 151 2015

6. J. Kim, F.Rousseau and M.Vazirgiannis, Convolutional

Sentence Kernel with Word Embedding for Short Text

Categorization, proceedings of the 2015 Conference on

Empirical Methods in Natural Language Processing (EMNLP

'15).

7. F. Rousseau, E. Kiagias and Michalis Vazirgiannis, Text

Categorization as a Graph Classification Problem, Proceedings

of the 52th Annual Meeting of the Association for

Computational Linguistics and the 6th International Joint

Conference on Natural Language Processing (ACL-IJCNLP

'15).

8. F. Rousseau and Michalis Vazirgiannis. K-core on Graph-of-

words for Single-Document Keyword Extraction, European

Conference on Information Retrieval, Vienna, Austria, 2015

9. P. Meladianos, G. Nikolentzos, F. Rousseau, Y. Stavrakas, M.

Vazirgiannis, “Degeneracy-Based Real-Time Sub-Event

Detection in Twitter Stream“, in the proceedings of the AAAI-

ICWSM 2015 conference

© 2017 International World Wide Web Conference Committee (IW3C2),

published under Creative Commons CC BY 4.0 License.

WWW 2017 Companion, April 3-7, 2017, Perth, Australia. ACM 978-1-4503-4914-7/17/04.

http://dx.doi.org/10.1145/3041021.3055362

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